Sequence detection system calculator

ABSTRACT

A computer-readable medium contains instructions for controlling a computer system in the analysis of an experiment to detect RNA or DNA in a sample by receiving exported cycle threshold values (exported C T  values) for a plate of wells from a polymerase chain reaction system and then calculates the delta C T , the delta delta C T  and the relative transcriptional change for the sample. The results including the cycle threshold values inputted from the polymerase chain reaction system are then displayed.

BACKGROUND

The polymerase chain reaction (“PCR”) has revolutionized nucleic acidresearch by providing a rapid means of amplifying specific nucleic acidsequences from complex genetic samples without the need fortime-consuming cloning, screening and nucleic acid purificationprotocols. PCR was originally disclosed and claimed by Mullis et al. inU.S. Pat. Nos. 4,683,195, 4,683,202, and 4,965,188, hereby incorporatedby reference. Since that time, considerable advances have been made inthe reagents, equipment and techniques available for PCR. These advanceshave increased both the efficiency and utility of the PCR reaction,leading to its adoption to an increasing number of different scientificapplications and situations.

The earliest PCR techniques were directed toward qualitative andpreparative methods rather than quantitative methods. PCR was used todetermine if a given sequence was present in any quantity at all or toobtain sufficient quantities of a specific nucleic acid sequence forfurther manipulation. Originally, PCR was not typically employed tomeasure the amount of a specific DNA or RNA present in a sample. Only inrecent years has quantitative PCR come to the forefront of nucleic acidresearch.

PCR amplification of a specific segment of DNA, referred to as thetemplate, requires that the nucleotide sequence of at least a portion ofeach end of the template be known. From the template, a pair ofcorresponding synthetic oligonucleotide primers (“primers”) can bedesigned. The primers are designed to anneal to the separatecomplementary strands of template, one on each side of the region to beamplified, oriented with its 3′ end toward the region between theprimers. The PCR reaction has the DNA template along with a large excessof the two oligonucleotide primers and each deoxyribonucleosidetriphosphate, a thermostable DNA polymerase and an appropriate reactionbuffer. To effect amplification, the mixture is denatured by heat tocause the complementary strands of the DNA template to disassociate. Themixture is then cooled to a lower temperature to allow theoligonucleotide primers to anneal to the appropriate sequences on theseparated strands of the template. Following annealing, the temperatureof the reaction is adjusted to an efficient temperature for 5′ to 3′ DNApolymerase extension of each primer into the sequences present betweenthe two primers. This results in the formation of a new pair ofcomplementary strands. The steps of denaturation, primer annealing andpolymerase extension can be repeated many times to obtain a highconcentration of the amplified target sequence. Each series ofdenaturation, annealing and extension constitutes one “cycle.” There maybe numerous “cycles.” The length of the amplified segment is determinedby the relative positions of the primers with respect to each other, andtherefore, this length is a controllable parameter. By virtue of therepeating aspect of the process, the method is referred to as the“polymerase chain reaction” (hereinafter “PCR”).

As the desired amplified target sequence becomes the predominantsequence in terms of concentration in the mixture, this sequence is saidto be PCR amplified. With PCR, it is possible to amplify a single copyof a specific target sequence in genomic DNA to a level detectable byseveral different methodologies. These methodologies include ethidiumbromide staining, hybridization with a labeled probe, incorporation ofbiotinylated primers followed by avidin-enzyme conjugate detection, andincorporation of ³²P-labeled deoxynucleotide triphosphates such as dCTPor DATP into the amplified segment. In addition to genomic DNA, anyoligonucleotide sequence can be amplified with the appropriate set ofprimer molecules. In particular, the amplified segments created by thePCR process are efficient templates for subsequent PCR amplificationsleading to a cascade of further amplification. Furthermore,amplification of RNA into DNA can be accomplished by including a reversetranscription step prior to the start of PCR amplification.

Prior to the development of real-time PCR, hybridization techniques weremost commonly used for the quantification of specific nucleic acids. Thehybridization signals in the test sample would be compared to similarsignals in serial dilutions of samples of known concentration. However,hybridization can be a time consuming process and requires large amountsof starting material.

While the potential application of PCR to the quantification of nucleicacid sequences was recognized almost immediately following itsdevelopment, numerous technical difficulties delayed the acceptance ofquantitative PCR as a reliable technique. Theoretically, each strand oftemplate DNA should be copied during PCR amplification, resulting in theexponential amplification of the target sequence. In practice, however,not every template is copied during each cycle.

Other technical difficulties such as the presence of competing templatesor the presence of inhibitors in the template sample can delay theexponential phase of the amplification for several cycles. In latercycles, the rate of DNA amplification begins to plateau as thedeoxyribonucleoside triphosphates and primers are incorporated into thetemplate and become limited in concentration. As a result,quantification of product is most reliable if measured during theexponential phase of DNA amplification. However, because of variationsin the quantity and quality of the DNA template and in the efficiency ofannealing between different sequences, it is difficult to predict thetiming and duration of the exponential phase of amplification.

Early attempts to achieve verifiably quantitative PCR involved thecreation of standardized curves by stopping the reaction at variouspoints and removing aliquots from the reaction. In this manner, the rateof amplification could be plotted to identify the exponential phase ofamplification. However, detection of product in the early stages ofamplification required radioactive labeling with all of its inherenttechnical difficulties and hazards. In addition, multiple dilutions ofthe template and multiple samplings were often necessary to obtain alinear standard curve, resulting in the need for multiple reactions. Asa result, these methods were costly in terms of template and reagent aswell as tedious to perform. Competitive PCR was developed in an attemptto solve these problems.

In competitive PCR, two templates are included in each PCR reaction, acontrol template of known concentration and a test template of unknownconcentration. The control template may have nearly the same sequence asthe test template but varies enough to be independently detectable. Itmay differ in size or may have point mutations or restriction sites notpresent in the test template. After the PCR reaction is completed, theproduct yields are measured for each template and the amount of testtemplate is calculated from the known concentration of the controltemplate. This method, while a considerable improvement, still suffersfrom a number of limitations. Even though the differences between thecontrol template and test template are minor, these may still be enoughto alter the rate of amplification. However, at the same time, thecontrol template and test template may be similar enough that theindividual strands of the test and control products may associate witheach other to form heterodimers. In addition, competitive PCR works bestif the test and control DNA are present in nearly equal amounts. Thus,multiple dilutions are often still necessary with all the accompanyingincreased costs in terms of labor, reagents and starting materials.

The development of real-time PCR, also known as kinetic PCR, hasprovided an improved method for the quantification of specific nucleicacids. In real-time PCR, cycle-by-cycle measurement of accumulated PCRproduct is made possible by combining thermal cycling and fluorescencedetection of the amplified product in a single instrument. Because theproduct is measured at each cycle, product accumulation can be plottedas a function of cycle number. The exponential phase of productamplification is readily determined and used to calculate the amount oftemplate present in the original sample. A number of alternative methodsare currently available for real-time PCR

The original protocol developed by Grossman et al. (U.S. Pat. No.5,470,705, hereby incorporated by reference) used radioactive labels onthe probes but further refinements of the method have focused onself-quenching fluorescent probes. Originally, separation of theamplified products by electrophoresis or other methods was used tomeasure and calculate the amount of released label. This addedtime-consuming steps to the analysis. Furthermore, this end-stageanalysis of the reactions cannot be readily applied to real-time PCR.

In one current method, fluorogenic exonuclease probes for the real-timedetection of PCR products are used. This type of technology is capturedin the ABI Prism® 7700 Sequence Detection System and disclosed in Livaket al (U.S. Pat. No. 5,538,848 hereby incorporated by reference). In amodification of an existing method utilizing radioactive labels,fluorogenic exonuclease probes are designed to anneal to sequencesbetween the two amplification primers but contain one or morenucleotides that do not match at the 5′ end. The nonmatching nucleotidesare linked to a fluorescence donor. A fluorescence quencher ispositioned typically at the end of the probe. When the donor andquencher are in the same vicinity, the quencher prevents thefluorescence donor from emitting light.

Traditional fluorescence quenchers absorb light energy emitted by anexcited reporter molecule and release this energy by fluorescing at ahigher wavelength. Increased sensitivity in real-time detection can beachieved with dark quenchers such as dabcyl or the developed EclipseQuencher from Epoch Biosciences, Inc. The dark quenchers absorbfluorescent energy but do not fluoresce themselves, thus reducingbackground fluorescence in the sample. The dark quencher workseffectively against a number of red-shifted fluoropores such as FAM, Cy3and Tamra due to its broader range of absorbance over dabcyl (400-650 nmversus 360-500 nm respectively) and is thus better suited to multiplexassays.

The sensitivity of real-time PCR can also be augmented through the useof minor groove binders (“MGBs”) (also from Epoch Biosciences, Inc.),which are certain naturally occurring antibiotics and syntheticcompounds able to fit into the minor groove of double-stranded DNA tostabilize DNA duplexes. The minor groove binders can be attached to the5′ end, 3′ end or an internal nucleotide of oligonucleotides to increasethe oligonucleotide's temperature of melting, i.e., the temperature atwhich the oligonucleotide disassociates from its target sequence andhence creates stability. The use of MGBs allows for the use of shorteroligonucleotide probes as well as the placement of probes in AT-richsequences without any loss in oligonucleotidal specificity, as well asbetter mismatch discrimination among closely related sequences. Minorgroup binders may be used in connection with dark quenchers or alone.

Thermus aquaticus (taq) DNA polymerse used for the PCR amplification hasthe ability to cleave unpaired nucleotides off of the 5′ end of DNAfragments. In the PCR reaction, the fluorogenic probe anneals to thetemplate (the nucleotide sequence of interest in a sample). An extensionof both primers and the probe occurs until one of the amplificationprimers is extended to the probe. Taq polymerase then cleaves thenonpaired nucleotides from the 5′ end of the probe, thereby releasingthe fluorescence donor. Once it is physically separated from thequencher, the fluorescent donor can fluorescence in response to lightstimulation. Because of the role of taq polymerase in this process,these probes are often referred to as TaqMan® probes. As more PCRproduct is formed, more fluorescent donors are released, allowing theformation of the PCR product to be measured and plotted as a function ofcycle time. The linear, exponential phase of the plot can be selectedand used to calculate the amount of nucleotide in the sample. Thedevelopment of these self-quenching fluorescent probes was aconsiderable advancement in quantitative PCR. Numerous improvedself-quenching probes and methods for the use thereof have beensubsequently reported in U.S. Pat. Nos. 5,912,148, 6,054,266 (Kronick etal.) and U.S. Pat. No. 6,130,073 (Eggerding).

The LightCycler® uses hybridization instead of exonuclease cleavage toquantitate the amplification reaction. This method also adds additionalfluorogenic probes to the PCR amplification. However, unlike the TaqMan®system, fluorescence increases in this system when two differentfluorogenic probes are brought together on the same template byextension or hybridization, allowing resonance energy transfer to occurbetween the two probes.

Other systems are also available. The Amplifluor® primers produced byIntergen® are hairpin oligonucleotides, which form hairpins when theyare single, stranded, which bring a fluorescence donor and quencher intoclose proximity. When the primers are incorporated into a doublestranded molecule, the hairpins are straightened, which separates thedonor and quencher to cause an increase in fluorescence.

Other applications make use of intercalating dyes, which only associatewith double stranded DNA. As more double stranded DNA is generated bythe reaction, more fluorescence is observed as more dye becomesassociated with DNA.

Regardless of the method used, the end result is the same, a plot offluorescence versus cycle number. Further analysis of this data is thenused to derive quantitative values for the RNA's present in the samples.Successful amplification of the sample will result in a sigmoidal plotconsisting of a period where amplification is not detectable above thebackground noise of the experiment, a period of exponentialamplification and a period where amplification plateaus. To analyze thedata, threshold value is selected that is greater than the backgroundnoise of the experiment. Each amplification curve is analyzed todetermine the point at which the curve rises above the threshold values.This is recorded in terms of the cycle in which this occurred and isknown as the threshold cycle (C_(T)).

As originally published in User Bulletin #2 for ABI Prisim 7700 SequenceDetection System, incorporated herein by reference, in the linear range(or exponential phase) the threshold cycle is inversely proportional tothe amount of RNA in a sample. These values can be compared to a plot ofthreshold cycles obtained from amplification of serial dilutions of anexogenously added standard to determine the concentration RNA in theexperimental samples. If the absolute quantity of the exogenously addedstandard is known, the absolute quantities of RNA in the experimentalsamples can be determined. However, the standard can also be of unknownconcentration, in which case, relative quantitation will be obtained.

The use of standard curves requires the amplification of exogenouslyadded nucleic acids, increasing the total number of amplificationsrequired and lowering the throughput of the experiment. Furthermore,because of variations in the quantity and quality of nucleic acidsbetween different samples, it is often beneficial to compare the amountof nucleic acid to an endogenous control. If an endogenous control ispresent, relative quantitation can be accomplished by mathematicalanalysis of the differences in cycle threshold between the experimentalsample and the endogenous control, eliminating the need for standardcurves and reducing the total number of amplification required in anexperiment. This mathematical analysis is performed by the humaninvestigator and can take weeks to prepare, publish and analyze. Auautomated way of preparing the data for analysis to meet thehigh-throughput requirements of today's drug discovery process islacking.

A need exists therefore, for an effective and efficient way of analyzingthe results of a high through put experiment to detect specific DNA orRNA transcripts.

SUMMARY OF THE INVENTION

The subject invention is a method in a computer system for analyzing anexperiment to detect RNA or DNA from a two dimensional plateconfiguration. The method comprises the steps of: (1) recordingexperiment information; (2) specifying at least one plate to theexperiment, each plate having a series of wells and dye layers and atleast one forward primer, probe, and reverse primer set (“FPR set”)categorized by dye layer or well; (3) populating at least one RNA group;(4) receiving exported experimental cycling results for each plateincluding a cycle threshold value (“C_(T)”) value for each FPR set ineach well; (5) calculating delta C_(T), delta delta C_(T), and relativetranscriptional change (XRel) values for each sample RNA; and (6)displaying the C_(T), the delta C_(T), the delta delta C_(T), and theXRel values for each sample RNA to detect RNA.

A computer-readable medium contains instructions for controlling acomputer system in the analysis of an experiment to detect RNA or DNA ina sample by receiving exported cycle threshold values (exported C_(T)values) for a plate of wells from a sequence detection system (alsoreferred to herein as “a polymerase chain reaction system”) and thencalculating the delta C_(T), the delta delta C_(T) and the relativetranscriptional change for the sample. The results including the cyclethreshold values inputted from the polymerase chain reaction system arethen published/displayed.

The present invention includes a computer readable program embodied in acomputer readable medium for analyzing data from any two dimensionalplate configurations, such as 96-well plates, 96-well custom plates,384-well plates and 384-well custom cards. The computer program of thesubject invention may also be used with an information-displayapparatus. The program rapidly calculates the delta C_(T), delta deltaC_(T) and XRel values for each dye layer of each well of a plate savingweeks of time in the analysis.

In the method of the present invention, any plate layout, unlimitednumbers of RNAs and unlimited numbers of primer/probe sets in anexperiment are acceptable. Data may be analyzed from a partial plate,single plate or multi-plate experiment. Single dye or multiplex analysis(not limited to two dyes) may be accommodated.

Exported results from any assay may be used for calculation. Output maybe published in an Excel spreadsheet format and the like or oninformation-display apparatus. The output includes the delta C_(T), thedelta delta C_(T), and the relative change in transcription or relativeexpression values (XRel). The method of this invention provides theflexibility to choose which FPR set is treated as the endogenous controlwhen multiplexing, and which RNA group is treated as the comparatorgroup, making it possible to compare reports with different endogenouscontrol/comparator group combinations. In addition, the % CV betweenreplicate wells on a plate is calculated and outlier replicates areflagged. The method of the subject invention may also be used togenerate the mean, standard deviation, and standard error of the meanamong RNA groups.

Experiment analysis using the method of the subject invention involves aseries of steps. Each step includes specifying certain information inorder to create file formats that receive exported cycle thresholdvalues for a given plate of wells, later used to calculate the deltaC_(T), the delta delta C_(T) and the relative transcription change(XRel).

As further described below, in the first step, experiment information isdefined such as a description, number of dye layers and otherparameters. Plate size, real or virtual plates and standard or customcards is then specified as plate information. The plate layout includingdrawing the plates or copying the layout of existing plates is added tothe plate information. FPR sets, RNA, and well type may also be part ofthe plate layout information provided. RNA is assigned to a group asgroup information. An endogenous control may be selected and the fileinformation saved. Raw data from the PCR system is then viewed andoutliers set. The delta C_(T), the delta delta C_(T) and the relativetranscription change are calculated, and these values are thenpublished.

BRIEF DESCRIPTION OF SEVERAL VIEWS OF THE DRAWINGS

For better understanding of the invention and to show by way of examplehow the invention may be carried into effect, reference is now made tothe detail description of the invention along with the accompanyingfigures in which corresponding numerals in the different figures referto corresponding parts and in which:

FIG. 1 is a logic flow diagram depicting the overall methodology of thepresent invention.

FIG. 2 is a logic flow diagram depicting step 1, experiment information.

FIG. 3 is a logic flow diagram depicting step 2, plate information.

FIG. 4 is a logic flow diagram depicting step 3, plate layout.

FIG. 5 is a logic flow diagram depicting step 4, group information.

FIG. 6 is a logic flow diagram depicting step 5, file information.

FIG. 7 is a logic flow diagram depicting step 6, raw data and outliermanagement.

FIG. 8 is a logic flow diagram depicting step 7, calculation.

FIG. 9 is a logic flow diagram depicting step 8, publish.

DETAILED DESCRIPTION

The present invention is a method in a computer system for analyzing anexperiment to detect RNA or DNA from a two-dimensional plateconfiguration. A computer-readable medium contains instructions forcontrolling a computer system in the analysis of an experiment to detectRNA in a sample. The computer usable medium has a computer readableprogram code embodied therein for determining the presence of RNA in asample contained within a dye layer of a well of a plate. A programstorage device readable by a computer, tangibly embodies the program ofinstructions is executed by the computer and performs the method stepsfor analyzing the presence of RNA in a sample. Also provided is acomputer-readable medium containing a data structure. A memory forstoring data for access by the computer program comprises the datastructure.

The present invention is suitable for any two-dimensional plateconfiguration including but not limited to 96-well plates, 384-wellplates, custom or standardized. The invention has the capability toanalyze data from a partial plate, single plate or multi-plateexperiment. Single dye or multiple dye (multiplexed) analysis can alsobe accommodated. The computer readable program code will accept anyplate layout, unlimited number of RNA samples and unlimited number ofprimer/probe sets (FPR sets) in an experiment. Exported result filesfrom any experiment run can be loaded into the program for calculation.

As part of the subject invention, the user may choose which FPR set istreated as the endogenous control and which RNA group is treated as thecomparator group, making it possible to compare reports with differentendogenous control and comparator group combinations. In addition,percent CV (% CV) between replicate wells on a plate may be calculatedand outlier replicates are flagged. The mean, standard deviation, andstandard error of the mean among RNA groups may also be calculated.

As further described below, experiment analysis involves a series ofsteps. The results of the analysis may be displayed in a Microsoft excelworkbook and the like or on an information-display apparatus.

To facilitate the understanding of this invention, a number of terms aredefined below. Terms defined herein have meanings as commonly understoodby a person of ordinary skill in the areas relevant to the presentinvention. Terms such as “a”, “an” and “the” are not intended to referto only a singular entity, but include the general class of which aspecific example may be used for illustration. The terminology herein isused to describe specific embodiments of the invention, but their usagedoes not limit the invention, except as outlined in the claims.

As used throughout the present specification the following abbreviationsare used:

-   -   C_(T) means threshold cycle value and is the cycle during PCR        when there is a detectable increase in signal intensity or        fluorescence above baseline;    -   CV means the coefficient of variation that is calculated for        each set of replicate wells having the same group label, sample        ID, and gene;    -   ΔC_(T) (also referred to as “delta C_(T)”)=Mean (C_(T) values        for sample FPR)−Mean(C_(T) values Endogenous Control FPR)    -   ΔC_(T) Mean Vehicle (comparator group)=Mean(ΔC_(T) for all        amplifications of the FPR set in the comparator group)    -   ΔC_(T) Median Vehicle (comparator group)=Median(ΔC_(T) for all        amplifications of the FPR set in the comparator group)    -   ΔΔC_(T) (also referred to as “delta delta C_(T)”)=(ΔC_(T) for        the sample, treated or diseased)−ΔC_(T) Median        Vehicle(comparator group)    -   E means to the efficiency of amplification for each experiment        and is assumed to be 1 (one);    -   FPR set means Forward Primer, Probe, and Reverse Primer Set used        to identify the presence of a gene;    -   −RT means Minus Reverse Transcriptase, an amplification used to        determine if DNA contaminants exist in the RNA. A −RT well        contains RNA and an FPR set, but does not contain reverse        transcriptase. Minus reverse transcriptase wells are related to        sample wells that have the same RNA and FPR set as the −RT well.    -   NTC means no template control and is a well that contains no        RNA;    -   PCR means polymerase chain reaction;    -   R_(n), normalized reporter signal and is determined to be the        signal activity of the reporter dye divided by the signal        activity of the passive reference dye;    -   RT means reverse transcriptase;    -   XRel means relative transcriptional change or relative        expression level of the gene.

Additional terms as used through the specification are defined asfollows:

Amplify when used in reference to nucleic acids refers to the productionof a large number of copies of a nucleic acid sequence by any methodknown in the art. Amplification is a special case of nucleic acidreplication involving template specificity.

Comparator or Comparator Group refers to sample used as the basis forcomparative results.

Dye refers to any fluorescent or non-fluorescent molecule that emits asignal upon exposure to light as apparent to those of skill in the artof molecular biology. The reporter dye refers to the dye used with thesample RNA.

Endogenous control refers to an RNA or DNA that is always present ineach experimental sample. By using an endogenous messenger RNA (mRNA)target can be normalized for differences in the amount of total RNAadded to each reaction. Typically, the endogenous control is ahousekeeping gene required for cell maintenance such as a gene formetabolic enzyme or the ribosomal RNA.

Exogenous control refers to a characterized RNA or DNA spiked into eachsample at a known concentration. An exogenous active reference isusually an in vitro construct that can be used as an internal positivecontrol (IPC) to distinguish true target negatives from PCR inhibition.An exogenous reference can also be used to normalize for differences inefficiency of sample extraction or complementary DNA (cDNA) synthesis byreverse transcriptase.

Experiment means a group of plates analyzed together;

Gene is used to refer to a functional protein, polypeptide orpeptide-encoding unit. As will be understood by those in the art, thisfunctional term includes genomic sequences, cDNA sequences, or fragmentsor combinations thereof, as well as gene products, including those thatmay have been altered by the hand of man. Purified genes, nucleic acids,protein and the like are used to refer to these entities when identifiedand separated from at least one contaminating nucleic acid or proteinwith which it is ordinarily associated.

Multiplexing PCR means the use of more than one dye layer in anexperiment and/or more than one FPR set with an associated reporter dyein each well of a plate. In one well, the target RNA and the endogenouscontrol are amplified by different FPR sets. All the wells on a plate inan experiment will always contain the same endogenous FPR set. If thereare three FPR sets used in the experiment, then all wells will have atleast one of those same three FPR sets unless the wells are empty wellson the plate. Each FPR set has an associated reporter dye. A C_(T) valueis reported for each FPR set in each well. A C_(T) value is recorded foreach dye layer in every well on the plate.

Notebook Page means a page in a notebook used to track experiments andother confidential information.

Nucleic acid refers to DNA, RNA, single-stranded or double-stranded andany chemical modifications thereof. Modifications include, but are notlimited to, those that add other chemical groups that provide additionalcharge, polarizability, hydrogen bonding, and electrostatic interaction.

Plate Consistency Control means a specified RNA, which is placed onevery plate in multiple plate experiments to ensure consistency acrossplates. Primer refers to an oligonucleotide, whether purified orproduced synthetically, which is capable of acting as a point ofinitiation of synthesis when placed under conditions in which synthesisof a primer extension product which is complementary to a nucleic acidstrand is induced, (i.e., in the presence of nucleotides and an inducingagent such as DNA polymerase and at a suitable temperature and pH). Theprimer may be single stranded for maximum efficiency in amplificationbut may alternatively be double stranded. If double stranded, the primeris first treated to separate its strands before being used to prepareextension products. The primer must be sufficiently long to prime thesynthesis of extension products in the presence of the inducing agent.The exact lengths of the primers will depend on many factors, includingtemperature, source of primer and the use of the method.

Probe refers to any compound which can act upon a nucleic acid in apredetermined desirable manner, including a protein, peptide, nucleicacid, carbohydrate, lipid, polysaccharide, glycoprotein, hormone,receptor, antigen, antibody, virus, pathogen, toxic substance,substrate, metabolite, transition state analog, cofactor, inhibitor,drug, dye, nutrient, growth factor, cell. It also refers to a sequenceof nucleotides, whether purified or produced synthetically,recombinantly or by PCR amplification, which is capable of hybridizingto another nucleotide sequence of interest. A probe may besingle-stranded or double-stranded. Probes are useful in the detection,identification and isolation of particular gene sequences. It iscontemplated that any probe used in the present invention will belabeled with a “reporter molecule,” so that is detectable in anydetection system including, but not limited to, enzyme (e.g. ELISA, aswell as enzyme-based histochemical assays), fluorescent, radioactive,and luminescent systems. It is not intended that the present inventionbe limited to any particular detection system or label.

Reference refers to a passive or active signal used to normalizeexperimental results. Endogenous and exogenous controls are examples ofactive references. Active reference means the signal is generated as aresult of PCR amplification. The active reference has its own set ofprimers and probe.

Sample RNA or sample refers to single or double stranded RNA used in oneor more experiments that may be obtained from a donor such as a person,animal or cell culture. When from an animal or person, it may be fromvariety of different sources, including blood, plasma, urine, semen,saliva, lymph fluid, meningeal fluid, amniotic fluid, glandular fluid,and cerebrospinal fluid, or from solutions or mixtures containinghomogenized solid material, such as feces, cells, tissues, and biopsysamples. One RNA sample may be used to determine the expression of oneor more genes. The same set of genes is used with every sample in thesame experiment.

Standard refers to a sample of known concentration used to construct astandard curve.

Vehicle refers to substances that are injected into an animal ascarriers for a test compound. Common vehicles include water, salinesolutions, physiologically compatible organic compounds such as variousalcohols, and other carriers well known in the art. Vehicle may alsorefer to a control animal injected with such a carrier in the absence ofa test compound. The vehicle animal serves as a control to mimictranscriptional alterations resulting from the stress of administrationbut not from the drug itself.

Calculations

As further described below in detail, the following calculations areused in connection with the subject invention:% CV for C _(T) Values(Coefficient of Variation)=100*(StDev/Mean)

XRel (relative transcriptional change or relative expression level),This value is calculated as (1+E)(^(−ΔΔC) _(T) for FPR set), where Ereflects the amplification efficiency and is assumed to be 1. E isstored as an experiment parameter and can be changed if necessary forthe given experiment. XRel values greater than 1 (one) indicate moregene expression in the RNA sample than in the comparator group of theparticular gene. Similarly, XRel values less than 1 (one) indicate lessgene expression in the RNA sample than in the comparator group of theparticular gene.

-   -   Group XRel Mean=Mean (XRel of each amplification of the FPR set        in the group    -   Group XRel StDev=StDev(XRel of each amplification of the FPR set        in the group    -   Group XRel SEM=StDev(XRel of each amplification of the FPR set        in the group/(n)⁵, where n is the number of amplifications with        FPR set in the group    -   % CV XREL=100*XRel SEM*SQR_(T)(n)/XRel Mean, where n is the        number of RNAs in the group.

If the amplification primers are optimized for amplification efficiency(i.e. E=1), XRel, the amount of a nucleic acid sample normalized to anendogenous reference and relative to a comparator group can becalculated by the mathematical formula:XRel=2^(−ΔΔCT)

This above formula was derived in the following manner: The exponentialamplification resulting from a given PCR reaction can be represented bythe formula:X _(n) =X _(o)×(1+E _(X))^(n)where X_(n) is the number of sample molecules after n cycles, X₀ is theinitial number of sample molecules; E_(x) is the efficiency of sampleamplification; and, n is the number of cycles.

This formula is then used to calculate the amount of product present atthe threshold cycle, C_(T). The threshold cycle is the point at whichthe amount of sample rises above a set threshold, typically whereexponential amplification can be first detected above the backgroundnoise of the experiment. At this point, the amount of product is:X _(T) =X _(o)×(1+E _(X))^(C) ^(T,X) =K _(X)where X_(T) is the number of sample molecules at the threshold cycle,C_(T,X) is the cycle number at which the amount of sample exceeds thethreshold value, and K_(x) is a constant.

In addition, a similar formula can be used to calculate the amount ofamplified sample in the endogenous reference control reaction at itsthreshold cycle:R _(T) =R _(o)×(1+E _(R))^(C) ^(T,R) =K _(R)where R_(T) is the number of copies of the amplified endogenousreference at its threshold cycle, R₀ is the initial number of copies ofthe endogenous reference, E_(R) is the efficiency of amplification ofthe endogenous reference, C_(T,R) is the threshold cycle number for theendogenous reference, where the amplified reference exceeds thethreshold value, and K_(R) is a constant for the endogenous reference.

The number of sample molecules (X_(T)) at the sample threshold cycle isthen divided by the number of endogenous reference molecules at thereference threshold cycle to yield a constant designated as K:$\frac{X_{T}}{R_{T}} = {\frac{X_{o} \times \left( {1 + E_{X}} \right)^{C_{T,X}}}{R_{o} \times \left( {1 + E_{R}} \right)^{C_{T,R}}} = {\frac{K_{X}}{K_{R}} = K}}$The constant, K, is not necessarily equal to one because the exactvalues of X_(T) and R_(T) can vary for a number of reasons depending onthe reporter dyes used in the probes, differential effects of probesequences on the fluorescence of the probes, the efficiency of probecleavage, the purity of the probes, and the setting of the fluorescencethreshold.

If the amplification efficiencies of the sample and endogenous referenceare assumed to be the same, i.e. E_(X)=E_(R)=E, the previous equationcan be simplified to:${\frac{X_{o}}{R_{o}} \times \left( {1 + E} \right)^{C_{T,X} - C_{T,R}}} = K$which can be rewritten as:X _(N)×(1+E)^(ΔC) ^(T) =Kwhere X_(N) is the normalized amount of sample (X₀/R₀); and ΔC_(T) isthe difference in threshold cycles for the sample and reference(C_(T,X)-C_(T,R)). The equation can be rearranged as follows:X _(N) =K×(1+E)^(−ΔC) ^(T)

XRel is then obtained by dividing normalized amount of sample relativeto endogenous control by the normalized amount of comparator relative toendogenous control as represented by the equation:$\frac{X_{N,q}}{X_{N,{cb}}} = {\frac{K \times \left( {1 + E} \right)^{{- \Delta}\quad C_{T,q}}}{K \times \left( {1 + E} \right)^{{- \Delta}\quad C_{T,{cb}}}} = \left( {1 + E} \right)^{{- {\Delta\Delta}}\quad C_{T}}}$where the ΔΔC_(T)=ΔC_(T,q)−ΔC_(T,cb). If the FPR sets are properlyoptimized for amplification efficiency, E should be nearly equal to oneand the equation can be simplified to:XRel=2^(−ΔΔC) ^(T)

For a given experiment, sample RNA may be obtained from a variety ofsources. It may be animal tissue from a particular organ or animal bloodor it might be from cell cultures. Regardless, there is usually morethan one sample having the same characteristic. The commoncharacteristic may be the type of treatment received (vehicle,compounds, etc.), the species, sex or age of the donor, or some othersimilar treatment. A group label is assigned to each group of samplessharing the same characteristic. Cell culture experiments in which eachwell on the cell culture plate is treated differently and not replicatedon another cell culture plate, will result in only one sample per group.Statistical analysis assumes there is more than one sample per group andthat each sample is independent of other samples treated in the samemanner.

One of the groups must be identified as the comparator group. It isoften the vehicle or untreated group. The comparator group may also be aparticular age or time point in the experiment. The comparator group isthe one group which all other groups in that experiment will becompared. For example, the comparator group may be untreated or normalsample to which the treated or diseased samples are compared. Allrelative expression values are defined relative to the comparator groupas being either the same, higher or lower than the comparator group.

Occasionally in an experiment, there may be a need to calculate relativeexpression values several times using more than one comparator group.For example, it may be necessary to see the relative fold changes in amessage compared to different time points in an experiment thus creatingthe need to easily be able to change the comparator group and quicklyrecalculate the relative expression values.

To run the experiment to detect RNA in the sample, the currenttechnology of either 96 or 384 well plates may be used. C_(T) values ofeach well are typically supplied by the manufacturer of the polymerasechain reaction system (otherwise referred to herein as the sequencedetection system). Each well may be identified as containing sample RNAor one of several types of assay controls.

There may be one or more types of control wells on each plate, or theremay be no control wells. The most common type of control occurs when theexperiment is performed on more than one plate, and will therefore becalled the plate control. The plate controls have the same source of RNAon all the plates and are monitored to determine whether there isconsistency in results across plates. The plate control may be one ofthe samples for which there is sufficient RNA to repeat it on all of theplates. Another type of control well is called the no template control,or NTC where no RNA is present. Thus, this control is used to determinethe background signal. A third type of control well is called minusreverse transcriptase control, or −RT. These wells contain no reversetranscriptase. Thus, this control is used to check whether DNAcontaminants are present in the RNA preparation.

If there are multiple plates and custom cards are not used, there shouldbe plate controls on each plate. These RNA controls are usually matchedto each gene (including endogenous) by being in the same rows or samecolumns as the RNA samples for that gene.

All samples and controls are replicated, having two or more wells foreach sample or control. The replicates must be on the same plate andwill usually be in the same row or the same column.

The RNA samples may be tested for the expression of one or more genes.The same set of genes is used with every sample in the same experiment.There will be matching endogenous control wells for each set of genewells on the same plate that will be used in the calculations. The mostcommon endogenous control is cyclophilin. These endogenous controls willusually be in the same rows or the same columns as the gene sample. If asample is run for multiple genes on the same plate, the same endogenouscontrol is used for all genes. If more than one endogenous control ispresent, only one will be identified for use in the calculations.

An exception occurs when custom plates are used. For example, one RNAsample may be analyzed for the transcription levels of genes plus oneendogenous control. Having the endogenous control contained in the samewell as the gene is called multiplexing.

Preferably, each well is specified by the following information:

-   -   1) well location on the plate or custom card,    -   2) sample type (unused, assay control, RNA sample, or both assay        control and RNA sample),    -   3) group label (such as treatment group, species, sex, age, type        of control, etc.),    -   4) sample ID (usually a number) within the group,    -   5) number of the FPR set(s) that identifies the gene(s).

If the sample type is assay control, the group label will identify thetype of control as either plate RNA control, NTC, or −RT. The sample idfield may be used to indicate the particular RNA sample corresponding tothe control. For example, each RNA (sample ID) may have a −RTcorresponding to it to check for DNA contamination in that samplepreparation. The FPR set number identifies the gene label for the plateRNA, NTC, or −RT control results and graphs.

For the RNA samples, the sample ID may be an RNA ID from remote databaseor an assigned name or number. There may be two FPR set numbers for thesame well, one for the endogenous control and one for the gene, ifmultiplexing is being performed, as in custom cards. Multiplexing can bedone on regular samples or on custom plates but is not necessarily doneon either.

If statistical comparisons are going to be made among groups, wheneverpossible, it is desirable to have the samples for the various groups onthe same plate. However, it is understood that this type of plate setupis not always possible. The coefficient of variation (100× standarddeviation/mean), or CV, may be calculated for each set of replicatewells having the same group label, sample ID, and gene. The welllocations of sets of wells where the CV exceeds a default value(currently 2% but may be lower), or a value that is specified by theuser, are shown. The user may than choose whether to delete one or moreof these wells from further processing.

The average of the replicate values is calculated for each assaycontrol, endogenous control, and gene. A ΔC_(T) (delta C_(T)) value iscalculated for each RNA sample/gene combination as the average C_(T) forthe gene minus the average C_(T) for the endogenous control for thatsample.

The calculations described so far can be performed at the plate level.The rest of the calculations require the data for all the plates to beavailable. All of the samples for the comparator group may not be on thesame plate. Also, the samples for the comparator group may or may not beon the same plate as the samples for the other groups.

The median of the C_(T) values is determined for all the samples in thiscomparator group, regardless of plate location. Then a ΔΔ(delta deltaC_(T)) value is calculated as the ΔC_(T) value for each sample minus themedian (middle or average of two middle values) ΔC_(T) value for thecomparator group.

As mentioned above, the relative transcriptional change (or relativeexpression level), XRel, is calculated as (1+E)^((−ΔΔCT)). E reflectsthe amplification efficiency and defaults to 1. Since ΔΔC_(T) will beabout zero for the comparator group, its XRel value will be close to 1.XRel values greater than 1 indicate more expression than the comparatorgroup while XRel values less than 1 indicate less expression than thecomparator group by the particular gene.

There are special rules for multiplexing. When multiplexing, any givenFPR set cannot exist in more than one combination of FPR sets. Forexample, if Gene 2 exists in a well with Gene 1 and the endogenouscontrol (“EndoC_(T)”), then Gene 2 can ONLY exist in wells alsocontaining Gene 1 and the endogenous control (“EndoC_(T)”). Gene 2cannot exist in a well of any other combination. For example, Gene 2cannot exist in a well containing Gene 3 and the EndoC_(T). Anymultiplexing experiment not following this rule will result in thereporting of invalid calculations. Below is an example of two plates.Plate 1 is a valid multiplexing experiment, while Plate 2 is not a validmultiplexing experiment. Endo, Gene1, Gene2 Endo, Gene1, Gene2 Endo,Gene3, Gene4 Endo, Gene3, Gene4 PLATE 1: Multiplexing (valid case) RNA1CTe, CTg1, CTg2 CTe, CTg1, CTg2 CTe, CTg3, CTg4 CTe, CTg3, CTg4 RNA2CTe, CTg1, CTg2 CTe, CTg1, CTg2 CTe, CTg3, CTg4 CTe, CTg3, CTg4 RNA3CTe, CTg1, CTg2 CTe, CTg1, CTg2 CTe, CTg3, CTg4 CTe, CTg3, CTg4 PLATE 2:Multiplexing (invalid case - Gene2 is a part of more than one FPR setcombination) RNA1 CTe, CTg1, CTg2 CTe, CTg1, CTg2 CTe, CTg2, CTg3 CTe,CTg2, CTg3 RNA2 CTe, CTg1, CTg2 CTe, CTg1, CTg2 CTe, CTg2, CTg3 CTe,CTg2, CTg3 RNA3 CTe, CTg1, CTg2 CTe, CTg1, CTg2 CTe, CTg2, CTg3 CTe,CTg2, CTg3

There are various levels of documentation and display of information.From the PCR system, typically a printout or other display is obtainedthat shows the details of the C_(T) values for each well on the plate.The present invention calculates and displays from these values shouldshow, by gene, the C_(T), ΔC_(T), ΔΔC_(T), and XRel values for eachsample in each group.

In addition, a summary may be shown for each group and gene thatcontains the descriptive statistics for the group (n, mean, and standarderror of the mean). A graph may be produced for each gene that displaysthe group means (with error bars). Furthermore, an electronic outputfile should be generated that contains the XRel values for each samplealong with the gene label, group label, and sample id. This output filecan then be used for further statistical analysis.

More detailed database files may be produced using the original platereader values so that, if desired, the calculations may be re-done,exercising different options. Graphics may be produced for assayvalidation purposes. Assuming that the C_(T) values are available on thesame plate for endogenous control samples and assay controls, a graph isproduced whose X-axis may display the C_(T) average of the endogenouscontrol wells that were used to calculate ΔC_(T) for all of the genes onthe plate. The Y-axis may then display the C_(T) values for the varioustypes of assay control wells, by gene, including endogenous. The symbolprinted reflects the gene label, as described in a legend. There may beas many of each symbol as there are plates in the assay.

If assay control samples are not available, a bar chart of endogenouscontrol wells may be provided. The bar for each plate reflects the mean,while the error bars reflect the minimum and maximum C_(T) values.Similar tables and graphs may also be produced for NTC and −RT controls.

In a preferred embodiment of the subject invention, an experimentbrowser is used as a navigation tool for processing the steps necessaryto analyze the experiment. Each step in the process is displayed on thebrowser. As the user completes a step in the process, that step ismarked as complete. This allows the user to determine which steps needto be completed before results can be produced by the calculation step.The experiment browser also provides the following functionality:

-   -   Find an existing experiment    -   Create a new experiment    -   Delete an experiment    -   Calculate experiment results    -   Publish experiment results    -   Remove experiment results    -   Navigation for processing steps

Preferably, all users may view all experiments. For example, theexperiment owner is often the only user allowed to modify any data forthe experiment. It is preferably that certain privileges be establishedto edit or view a current experiment.

To navigate, the experiments are grouped by year, and month. A foldermay be displayed for each year and month for which, based on the findcriteria, an experiment exists. Experiments are then preferably orderedby a unique experiment id within each folder. Folders may then beexpanded or collapsed. To edit, the appropriate screen is displayed foreach step.

In order to work with an experiment in the experiment browser, thedesired experiment data must be available is and is preferably retrievedfrom a remote database. The user may search a database for a particularexperiment using experimental criteria or gene criteria or anycombination thereof The experiment criteria pertain to a specificexperiment. Hence, experiments that match the criteria entered will beretrieved. Example experiment criteria include experiment ID, notebookpage, run date and owner. The experiments that match the criteria may beconveniently displayed and viewed below the search criteria.

Gene criteria include criteria pertaining to the species, gene andforward primer, probe, and reverse primer set used in an experiment.Experiments that match the criteria entered will be retrieved anddisplayed, preferably below the search criteria.

As shown in FIGS. 1 to 9, the method of the subject invention comprisesa number of specific steps. FIG. 1 depicts the overall methodology ofpresent invention.

FIG. 2 is a flow chart of the first step, the recording of experimentinformation. To create a new experiment, a separate screen is displayedand information provided such as experiment ID, description, dye layersand other parameters including notebook page reference, outlier cutoff,and amplification efficiency “E.” Experiments can also be deleted fromthe database. However, it is recommended that a privilege be attached tothis function.

In the step 2, plate information including the number of plates and typeof plates are specified. FIG. 3 is a flow chart of this second step.Real or virtual plates may be specified. A virtual plate may be a platefrom a previous experiment. Plates of varying size may be selected. Fora new experiment there are initially no plates defined. Plates may beadded to the experiment in an unlimited number as real or virtualplates.

Real plates are the new plates defined for the current experiment. Datafiles gathered at the time of the experiment shall be parsed andrecorded under the appropriate plate. A type of plate is also chosensuch as 96 well or 384 well plate or custom card.

Virtual plates are plates that already exist on another experiment. Thedata for these plates was gathered on the other experiment. Virtualplates are optional.

For example, the first experiment is at time zero, the second experimentis at time 3 months, and the third and current experiment at time 6months. The analysis for this current experiment would include the platedate from the previous two experiments, time zero and time 3 months. Thecurrent experiment, time 6 months, would then include its own plates(real plates), along with the plates from the previous two experiments,time zero and time 3 months, as virtual plates. When adding virtualplates to an experiment, the dyes used on the virtual plate must matchthe dyes for the experiment. For example, an experiment defined as usingthe FAM dye cannot have a virtual plate using the VIC dye.

When specifying plate information, information about the particularplate is included such as number of wells, well type, dye layers, andFPR set. The contents of the well or well type may be minus RT, plateconsistency control, sample, and sample and plate consistency control.Each well either contains RNA or is NTC. All wells that are not emptycontain an FPR set.

In Step 3, and as shown in FIG. 4, the plate layout including definingFPR sets and RNA associated to each well on the plate for the experimentis provided. Prior to generating this information, both experimentinformation and plate information must have been completed. The FPR setsare categorized by dye layer and species. To apply an FPR set, selectthe wells of interest and select the desired FPR set. Conversely, theremove an FPR set, select the wells of interest and delete or remove theFPR set from its designation.

If the experiment is multiplexed, only one FPR set per each dye layermay be used in each well. Dye layers are associated to the experimentthrough the experiment information. If the experiment is notmultiplexed, only one FPR set per well can be specified. When applyingFPR sets, if any of the selected wells already contain an FPR set theywill not be overridden with the FPR set that is currently selected. Toreplace an FPR set, the existing FPR set must be removed or deletedfirst.

RNA is categorized by the user and once recorded as part of an internaldatabase is referred to as registered. When the user changes, therelevant registered RNAs are listed. To apply registered RNA, select thewells of interest and the registered RNA. To remove registered RNA,select the wells of interest and delete the registered RNA. Only oneregistered RNA per well may be specified. Whey applying registered RNA,if any of the selected wells already contain registered RNA, they willbe overridden with registered RNA that is currently selected. To replaceregistered RNA, it must be removed. Registered RNA cannot be applied toNTC wells or empty wells.

To create unregistered RNA or RNA that has not been previously recorded,identify the number of unregistered RNA to generate. At this time, thename, notebook page and comments may be associated to the unregisteredRNA. This unregistered RNA information may be modified if necessary. Theunregistered RNA is then associated with wells of interest. Only oneunregistered RNA may be specified per well. Unregistered RNA will not beapplied to wells already containing unregistered RNA. The unregisteredRNA must be removed from a well prior to selecting another unregisteredRNA. Unregistered RNA may not be applied to NTC wells or empty wells.

A number of various well types are available for use in connection withthe method of the subject invention. The types of wells include, but arenot limited to, the following: sample, NTC, RT, plate consistency,sample and plate consistency, or empty. Plate information including FPRsets, registered RNA, unregistered RNA, and well type may be copied fromanother plate. In order to save plate information, wells of thefollowing types must contain RNA and FPR sets: Minus RT, Plateconsistency control, sample, and sample and plate consistency control.NTC wells must contain an FPR set. When multiplexing, all non-emptywells must share a common FPR set.

The next step (step 4) in the method of the subject invention is tocreate and populate RNA groups. FIG. 5 is a flow chart of this step. AnRNA group can be only one RNA but may contain multiple RNAs. Bothregistered and unregistered RNA are available to assign to groups. OnlyRNA belonging to a sample or sample and plate consistency wells isprovided here. Each new RNA group shall have a group name. Each specificRNA is assigned to a group and may be later removed if necessary. AllRNA must be assigned to at least one group.

In step 5, exported data files are associated to specific real plates inthe experiment. As shown in FIG. 6, the file information for virtualplates used in the experiment already exists and may be overwritten. Anyone of a number of data file formats may be utilized. If an endogenouscontrol was not specified, an endogenous control gene must be selectedat this time.

In step 6, C_(T) values may be reviewed and outliers managed. Outliersmay be calculated at any point, up to the time the experiment has beenpublished. As shown in FIG. 7, outliers may be turned on or off at thewell level for each dye layer. Two types of outliers exist includingauto outliers identified during the file information step and useroutliers explicitly set by the user. Several outlier values may beidentified at one time. When multiplexing, outliers may be viewed fordifferent dye layers. Once all dye layers have been accessed, outliersmay be saved or recalculated.

Outliers are determined by calculating the coefficient of variation, CV,for each set of replicate Ct values within the same RNA Group. Areplicate Ct value is defined as a sample well containing the same FPRSet and the same RNA. When multiplexing, a sample well may containmultiple Ct values. If the CV for a replicate Ct value exceeds apredetermined percentage, that Ct value is marked as a auto outlier.Marking a Ct value as an auto outlier indicates that the user shouldreview that Ct value for accuracy. If the user determines that the Ctvalue should not be included in any calculations, the user has theability to mark it as a user outlier. Marking a Ct value as a useroutlier prevents that value from being used in any calculations.

In step 7, as shown in FIG. 8, the calculations are completed. First,the endogenous control and comparative groups are selected. Theendogenous control and comparative groups are the basis behind thereported calculation for all genes. Choosing different comparativegroups is a unique feature of the method of the subject invention.Through this feature it is possible to compare delta delta C_(T) andXRel results with different comparative groups. The user may excludemarked outliers if necessary.

The endogenous control is initially selected by the user at the timedata are parsed for the experiment (step 5 described above). The autooutlier process is performed any time data are changed in experimentanalysis. The user may select a different endogenous control during thecalculations (step 7) of the analysis. If the endogenous control ischanged, the user may run the outlier process again to reflect a changein the endogenous control.

In order to determine the relative expression value of any given sample,one sample (RNA) or group of samples (group of RNAs) must be chosen as acomparator. The comparator group is one to which all other groups willbe compared. All relative expression values are defined relative to thecomparator group as being the same, higher or lower than the comparatorgroup.

Occasionally in an experiment, there may be a need to calculate relativeexpression values several times using more than one comparator group.For example, it may be necessary to see relative fold changes in amessage compared to different points in the experiment thus creating theneed to easily be able to change the comparator group and quicklyrecalculate the relative expression values.

The ability to chose different comparator groups is a feature of thesubject invention that makes it possible to compare ΔΔC_(T) and XRELresults using different comparator groups.

The following calculations are made with respect to each endogenouscontrol for each FPR set across all RNAs: mean, % CV and delta C_(T).Calculations for each comparator group include delta C_(T) mean andmedian. Across all RNAs with respect to the comparator group the deltadelta C_(T) and XRel for each FPR set is calculated. XRel Mean, XRelstandard deviation, XRel SEM and XRel % CV is calculated for each FPRset across all RNAs excluding endogenous control.

EXAMPLE 1 Experimental Analysis of the Expression of Four Genes in ThreeGroups

A gene expression experiment was performed analyzing the effects of twodifferent experimental conditions (Groups A and B) relative to a control(Group V) on the expression of five different genes (Genes 1-5). RNA wasisolated from seven replicates for the control and nine replicates forthe experimental conditions. After isolation, samples are subjected toreverse transcriptase PCR analysis. Each sample was amplified with anendogenous control FPR as well as the FPR's for each of the five genes.Note, this example is not multiplex; multiplex has more than one set ofprimers and probes in the same reaction well with each probe labeledwith a different fluorescent reporter dye. The analysis was performed induplicate for each sample, requiring a total of four plates to performall amplifications.

The analysis was initiated for five different genes under three separateexperimental conditions. Each experimental condition represents a group,which are encoded herein as Groups A, B and V. The genes are encodedherein as Gene 1, Gene 2, Gene 3, Gene 4 and Gene 5. The C_(T) value foreach well were exported. The exported data is shown below in Table 1.Table 1 contains the Ct values extracted from the data files in a formatthat represents the location of each Ct value on the plate. An EXCELworksheet may be created for each dye layer used in the experiment. Theworksheet contains the Ct values for each plate of the specified dyelayer. The C_(T) value for each well is shown relative to the positionof the well on the plate. Similar calculations are used to calculateΔC_(T) values for all of the samples in Groups A (Table 3) and Group B(Table 4). A summary of results calculated from an analysis of all fivegenes is provided in Table 5. TABLE 1 Plate 1 test 2a 15.83 16.03 27.0627.18 23.35 23.19 20.57 19.96 23.82 23.79 29.09 29.36 16.86 16.47 26.8627.04 23.35 23.72 21 20.64 22.78 22.3 28.78 28.43 16.3 16.08 27.18 27.4123.47 23.49 20.46 20.43 23.58 23.33 28.69 29.1 16.22 16.53 27.2 27.523.54 23.98 21.3 21.02 23.98 23.94 29.35 29.34 16.23 15.96 26.64 26.923.73 23.94 20.53 20.61 24.6 24.31 29.08 29.01 16.34 17.14 26.16 26.5323.67 23.42 21.2 21.37 25.22 25.25 29.03 29.1 16.46 16.63 25.16 24.6223.08 23.04 21.11 20.87 22.52 23.18 29.08 28.34 40 40 40 40 40 40 40 4040 40 40 40 Plate 2 Plate 371 15.78 16.46 27.28 27.11 23.14 23.46 20.120.29 23.24 23.64 28.08 28.47 15.82 16.25 23.04 23.32 18.89 18.42 18.8718.43 22.25 21.85 26.06 25.87 16.22 16.12 23.83 24.18 19.33 18.85 19.1618.77 22.22 22.33 26.61 26.55 15.45 15.99 22.84 23.25 18.62 18.46 18.2818.94 22.09 21.71 25.28 24.73 15.99 15.57 23.49 23.44 18.94 19.22 18.2118.44 22.33 22.76 25.17 25.02 15.53 16.07 24.99 24.55 19.47 19.54 19.4719.64 22.83 23.34 27.04 27.55 16.23 16.33 23.27 23.11 19.56 19.24 19.2519.26 22 22.12 26.97 26.66 40 40 30.13 40 40 40 40 40 40 40 40 40 Plate3 Plate 372 16.67 16.64 27.42 28.07 23.19 23.74 21.03 21.29 23.4 23.8129.15 29.21 16.55 16.4 24.5 24.68 19.04 19.25 20.31 19.68 23.37 23.2427.21 27.2 16.23 15.85 24.69 25.27 19.31 19.47 19.14 19.95 23.12 22.8326.48 26.49 16.65 16.34 25.44 25.7 19.03 18.56 21.59 21.99 24.98 24.9128.22 27.72 16.43 16.15 26.57 26.61 23.03 22.65 19.71 20.2 24.07 23.727.19 27.78 16.59 16.29 26.3 26.24 22.84 23.17 21.49 21.23 24.35 24.228.42 28.83 15.82 16.03 23.35 23.29 19.48 19.3 19.13 18.89 22.06 21.925.05 24.99 40 40 40 40 40 40 40 40 40 40 40 40 Plate 4 Plate 373 16.3116.08 26.97 26.52 23.4 23.28 20.56 20.22 23.11 23.21 28.41 28.36 16.0916.17 25.77 25.88 22.26 22.42 20.32 20.21 23.11 23.34 27.72 27.85 16.3516.81 24.77 24.81 21.48 21.51 19.81 20.16 22.66 22.86 27.69 28 16.1915.76 25.42 25.22 21.97 21.67 19.37 19.47 23.28 22.93 27.26 27.09 16.3916.73 26.22 26.04 21.02 21.4 19.3 19.56 23.38 23.31 27.31 27.15 16.5515.98 25.87 25.79 23.08 22.99 20.49 20.55 22.78 23.17 27.15 27.51 16.0616.31 25.76 25.64 22.05 21.71 20.68 20.27 23.88 23.74 27.99 28.53 40 4040 40 40 40 40 40 40 40 40 40

TABLE 2 Relative Sample Group Endo CT Avg CT % CV A* U** CT Avg CT % CVA* U** ΔCT ΔΔCT Quantitative 15.83 23.35 n 7 1 V 16.03 15.93 0.9 23.1923.27 0.5 7.34 0.05 0.97 MEAN 1.15 16.47 23.72 STDEV 0.34 4 V 16.8616.67 1.7 23.35 23.54 1.1 6.87 −0.42 1.34 SEM 0.13 16.08 23.49 5 V 16.3016.19 1.0 23.47 23.48 0.1 7.29 0.00 1.00 16.53 23.98 6 V 16.22 16.38 1.323.54 23.76 1.3 7.39 0.09 0.94 15.96 23.94 7 V 16.23 16.10 1.2 23.7323.84 0.6 7.74 0.45 0.73 17.14 X 23.42 8 V 16.34 16.74 3.4 X 23.67 23.550.8 6.81 −0.48 1.40 16.63 23.04 9 V 16.46 16.55 0.7 23.08 23.06 0.1 6.52−0.78 1.71 MEDIAN ΔCT Vehicle 7.29 MEAN ΔCT Vehicle 7.14

TABLE 3 Relative Sample Group Endo CT Avg CT % CV A* U** CT Avg CT % CVA* U** ΔCT ΔΔCT Quantitative 16.25 18.42 n 9 10 A 15.82 16.04 1.9 18.8918.66 1.8 2.62 −4.67 25.46 MEAN 20.66 16.12 18.85 STDEV 6.10 11 A 16.2216.17 0.4 19.33 19.09 1.8 2.92 −4.37 20.68 SEM 2.03 15.99 18.62 12 A15.45 15.72 2.4 18.46 18.54 0.6 2.82 −4.47 22.16 15.57 19.22 13 A 15.9915.78 1.9 18.94 19.08 1.0 3.30 −3.99 15.89 15.53 19.54 14 A 16.07 15.802.4 19.47 19.51 0.3 3.71 −3.59 12.00 16.33 19.24 15 A 16.23 16.28 0.419.56 19.40 1.2 3.12 −4.17 18.00 16.40 19.25 17 A 16.55 16.48 0.6 19.0419.15 0.8 2.67 −4.62 24.59 15.85 19.47 18 A 16.23 16.04 1.7 19.31 19.390.6 3.35 −3.94 15.35 16.34 18.56 36 A 16.65 16.50 1.3 19.03 18.80 1.82.30 −4.99 31.78

TABLE 4 Relative Sample Group Endo CT Avg CT % CV A* U** CT Avg CT % CVA* U** ΔCT ΔΔCT Quantitative 16.15 22.65 n 9 39 B 16.43 16.29 1.2 23.0322.84 1.2 6.55 −0.74 1.67 MEAN 4.25 16.29 23.17 STDEV 4.08 40 B 16.5916.44 1.3 22.84 23.01 1.0 6.57 −0.72 1.65 SEM 1.36 16.03 19.30 41 B15.82 15.93 0.9 19.48 19.39 0.7 3.47 −3.83 14.17 16.17 22.42 42 B 16.0916.13 0.4 22.26 22.34 0.5 6.21 −1.08 2.11 16.81 21.51 43 B 16.35 16.582.0 21.48 21.50 0.1 4.92 −2.38 5.19 15.76 21.67 44 B 16.19 15.98 1.921.97 21.82 1.0 5.85 −1.45 2.72 16.73 21.40 46 B 16.39 16.56 1.5 21.0221.21 1.3 4.65 −2.64 6.23 15.98 22.99 47 B 16.55 16.27 2.5 23.08 23.040.3 6.77 −0.52 1.43 16.31 21.71 48 B 16.06 16.19 1.1 22.05 21.88 1.15.70 −1.60 3.02

TABLE 5 Experiment ID: 99999 Description: Experiment Description Label:Experiment Label Experiment Date: 8/21/2001 Amplification Efficiency(E): 1 Outlier Cutoff (% CV): 3 Relative Dye Group Sample Gene Avg CT %CV ΔCT ΔΔCT Quantitative SEM Dye Layer 1 V 1 Endo 15.93 0.9 N/A N/A N/ADye Layer 1 V 1 Gene 1 23.27 0.5 7.34 0.05 0.97 Dye Layer 1 V 1 Gene 220.27 2.1 4.34 −0.11 1.08 Dye Layer 1 V 1 Gene 3 23.81 0.1 7.88 0.290.82 Dye Layer 1 V 1 Gene 4 29.23 0.7 13.30 0.59 0.66 Dye Layer 1 V 1Gene 5 27.12 0.3 11.19 0.51 0.70 Dye Layer 1 V 4 Endo 16.67 1.7 N/A N/AN/A Dye Layer 1 V 4 Gene 1 23.54 1.1 6.87 −0.42 1.34 Dye Layer 1 V 4Gene 2 20.82 1.2 4.16 −0.29 1.22 Dye Layer 1 V 4 Gene 3 22.54 1.5 5.88−1.71 3.27 Dye Layer 1 V 4 Gene 4 28.61 0.9 11.94 −0.77 1.70 Dye Layer 1V 4 Gene 5 26.95 0.5 10.29 −0.39 1.31 Dye Layer 1 V 5 Endo 16.19 1.0 N/AN/A N/A Dye Layer 1 V 5 Gene 1 23.48 0.1 7.29 0.00 1.00 Dye Layer 1 V 5Gene 2 20.45 0.1 4.26 −0.19 1.14 Dye Layer 1 V 5 Gene 3 23.46 0.8 7.27−0.32 1.25 Dye Layer 1 V 5 Gene 4 28.90 1.0 12.71 0.00 1.00 Dye Layer 1V 5 Gene 5 27.30 0.6 11.11 0.43 0.74 Dye Layer 1 V 6 Endo 16.38 1.3 N/AN/A N/A Dye Layer 1 V 6 Gene 1 23.76 1.3 7.39 0.09 0.94 Dye Layer 1 V 6Gene 2 21.16 0.9 4.79 0.34 0.79 Dye Layer 1 V 6 Gene 3 23.96 0.1 7.590.00 1.00 Dye Layer 1 V 6 Gene 4 29.35 0.0 12.97 0.26 0.83 Dye Layer 1 V6 Gene 5 27.35 0.8 10.98 0.30 0.81 Dye Layer 1 V 7 Endo 16.10 1.2 N/AN/A N/A Dye Layer 1 V 7 Gene 1 23.84 0.6 7.74 0.45 0.73 Dye Layer 1 V 7Gene 2 20.57 0.3 4.48 0.03 0.98 Dye Layer 1 V 7 Gene 3 24.46 0.8 8.360.77 0.58 Dye Layer 1 V 7 Gene 4 29.05 0.2 12.95 0.24 0.84 Dye Layer 1 V7 Gene 5 26.77 0.7 10.68 0.00 1.00 Dye Layer 1 V 8 Endo 16.74 3.4 N/AN/A N/A Dye Layer 1 V 8 Gene 1 23.55 0.8 6.81 −0.48 1.40 Dye Layer 1 V 8Gene 2 21.29 0.6 4.55 0.10 0.93 Dye Layer 1 V 8 Gene 3 25.24 0.1 8.500.91 0.53 Dye Layer 1 V 8 Gene 4 29.07 0.2 12.33 −0.38 1.30 Dye Layer 1V 8 Gene 5 26.35 1.0 9.61 −1.07 2.10 Dye Layer 1 V 9 Endo 16.55 0.7 N/AN/A N/A Dye Layer 1 V 9 Gene 1 23.06 0.1 6.52 −0.78 1.71 Dye Layer 1 V 9Gene 2 20.99 0.8 4.45 0.00 1.00 Dye Layer 1 V 9 Gene 3 22.85 2.0 6.31−1.28 2.43 Dye Layer 1 V 9 Gene 4 28.71 1.8 12.17 −0.54 1.45 Dye Layer 1V 9 Gene 5 24.89 1.5 8.35 −2.33 5.03 Dye Layer 1 A 10 Endo 16.04 1.9 N/AN/A N/A Dye Layer 1 A 10 Gene 1 18.66 1.8 2.62 −4.67 25.46 Dye Layer 1 A10 Gene 2 18.65 1.7 2.62 −1.83 3.56 Dye Layer 1 A 10 Gene 3 22.05 1.36.02 −1.57 2.97 Dye Layer 1 A 10 Gene 4 25.97 0.5 9.93 −2.78 6.84 DyeLayer 1 A 10 Gene 5 23.18 0.9 7.15 −3.53 11.55 Dye Layer 1 A 11 Endo16.17 0.4 N/A N/A N/A Dye Layer 1 A 11 Gene 1 19.09 1.8 2.92 −4.37 20.68Dye Layer 1 A 11 Gene 2 18.97 1.5 2.80 −1.65 3.14 Dye Layer 1 A 11 Gene3 22.28 0.3 6.11 −1.48 2.79 Dye Layer 1 A 11 Gene 4 26.58 0.2 10.41−2.30 4.91 Dye Layer 1 A 11 Gene 5 24.01 1.0 7.84 −2.84 7.16 Dye Layer 1A 12 Endo 15.72 2.4 N/A N/A N/A Dye Layer 1 A 12 Gene 1 18.54 0.6 2.82−4.47 22.16 Dye Layer 1 A 12 Gene 2 18.61 2.5 2.89 −1.56 2.94 Dye Layer1 A 12 Gene 3 21.90 1.2 6.18 −1.41 2.65 Dye Layer 1 A 12 Gene 4 25.011.6 9.29 −3.42 10.70 Dye Layer 1 A 12 Gene 5 23.05 1.3 7.33 −3.35 10.20Dye Layer 1 A 13 Endo 15.78 1.9 N/A N/A N/A Dye Layer 1 A 13 Gene 119.08 1.0 3.30 −3.99 15.89 Dye Layer 1 A 13 Gene 2 18.33 0.9 2.55 −1.903.73 Dye Layer 1 A 13 Gene 3 22.55 1.3 6.77 −0.82 1.77 Dye Layer 1 A 13Gene 4 25.10 0.4 9.32 −3.39 10.48 Dye Layer 1 A 13 Gene 5 23.47 0.2 7.69−2.99 7.94 Dye Layer 1 A 14 Endo 15.80 2.4 N/A N/A N/A Dye Layer 1 A 14Gene 1 19.51 0.3 3.71 −3.59 12.00 Dye Layer 1 A 14 Gene 2 19.56 0.6 3.76−0.69 1.61 Dye Layer 1 A 14 Gene 3 23.09 1.6 7.29 −0.30 1.23 Dye Layer 1A 14 Gene 4 27.30 1.3 11.50 −1.21 2.31 Dye Layer 1 A 14 Gene 5 24.77 1.38.97 −1.71 3.26 Dye Layer 1 A 15 Endo 16.28 0.4 N/A N/A N/A Dye Layer 1A 15 Gene 1 19.40 1.2 3.12 −4.17 18.00 Dye Layer 1 A 15 Gene 2 19.26 0.02.98 −1.47 2.77 Dye Layer 1 A 15 Gene 3 22.06 0.4 5.78 −1.81 3.49 DyeLayer 1 A 15 Gene 4 26.82 0.8 10.54 −2.17 4.50 Dye Layer 1 A 15 Gene 523.19 0.5 6.91 −3.77 13.59 Dye Layer 1 A 17 Endo 16.48 0.6 N/A N/A N/ADye Layer 1 A 17 Gene 1 19.15 0.8 2.67 −4.62 24.59 Dye Layer 1 A 17 Gene2 20.00 2.2 3.52 −0.93 1.90 Dye Layer 1 A 17 Gene 3 23.31 0.4 6.83 −0.761.69 Dye Layer 1 A 17 Gene 4 27.21 0.0 10.73 −1.98 3.93 Dye Layer 1 A 17Gene 5 24.59 0.5 8.12 −2.56 5.90 Dye Layer 1 A 18 Endo 16.04 1.7 N/A N/AN/A Dye Layer 1 A 18 Gene 1 19.39 0.6 3.35 −3.94 15.35 Dye Layer 1 A 18Gene 2 19.55 2.9 3.51 −0.94 1.92 Dye Layer 1 A 18 Gene 3 22.98 0.9 6.94−0.65 1.57 Dye Layer 1 A 18 Gene 4 26.49 0.0 10.45 −2.26 4.79 Dye Layer1 A 18 Gene 5 24.98 1.6 8.94 −1.74 3.33 Dye Layer 1 A 36 Endo 16.50 1.3N/A N/A N/A Dye Layer 1 A 36 Gene 1 18.80 1.8 2.30 −4.99 31.78 Dye Layer1 A 36 Gene 2 21.79 1.3 5.30 0.85 0.55 Dye Layer 1 A 36 Gene 3 24.95 0.28.45 0.87 0.55 Dye Layer 1 A 36 Gene 4 27.97 1.3 11.48 −1.23 2.35 DyeLayer 1 A 36 Gene 5 25.57 0.7 9.08 −1.60 3.03 Dye Layer 1 B 39 Endo16.29 1.2 N/A N/A N/A Dye Layer 1 B 39 Gene 1 22.84 1.2 6.55 −0.74 1.67Dye Layer 1 B 39 Gene 2 19.96 1.7 3.67 −0.78 1.72 Dye Layer 1 B 39 Gene3 23.89 1.1 7.60 0.01 0.99 Dye Layer 1 B 39 Gene 4 27.49 1.5 11.20 −1.512.85 Dye Layer 1 B 39 Gene 5 26.59 0.1 10.30 −0.38 1.30 Dye Layer 1 B 40Endo 16.44 1.3 N/A N/A N/A Dye Layer 1 B 40 Gene 1 23.01 1.0 6.57 −0.721.65 Dye Layer 1 B 40 Gene 2 21.36 0.9 4.92 0.48 0.72 Dye Layer 1 B 40Gene 3 24.28 0.4 7.84 0.25 0.84 Dye Layer 1 B 40 Gene 4 28.63 1.0 12.19−0.52 1.43 Dye Layer 1 B 40 Gene 5 26.27 0.2 9.83 −0.84 1.80 Dye Layer 1B 41 Endo 15.93 0.9 N/A N/A N/A Dye Layer 1 B 41 Gene 1 19.39 0.7 3.47−3.83 14.17 Dye Layer 1 B 41 Gene 2 19.01 0.9 3.09 −1.36 2.57 Dye Layer1 B 41 Gene 3 21.98 0.5 6.06 −1.53 2.89 Dye Layer 1 B 41 Gene 4 25.020.2 9.10 −3.61 12.21 Dye Layer 1 B 41 Gene 5 23.32 0.2 7.40 −3.28 9.71Dye Layer 1 B 42 Endo 16.13 0.4 N/A N/A N/A Dye Layer 1 B 42 Gene 122.34 0.5 6.21 −1.08 2.11 Dye Layer 1 B 42 Gene 2 20.27 0.4 4.14 −0.311.24 Dye Layer 1 B 42 Gene 3 23.23 0.7 7.10 −0.49 1.40 Dye Layer 1 B 42Gene 4 27.79 0.3 11.66 −1.05 2.07 Dye Layer 1 B 42 Gene 5 25.83 0.3 9.70−0.98 1.97 Dye Layer 1 B 43 Endo 16.58 2.0 N/A N/A N/A Dye Layer 1 B 43Gene 1 21.50 0.1 4.92 −2.38 5.19 Dye Layer 1 B 43 Gene 2 19.99 1.2 3.41−1.04 2.06 Dye Layer 1 B 43 Gene 3 22.76 0.6 6.18 −1.41 2.65 Dye Layer 1B 43 Gene 4 27.85 0.8 11.27 −1.44 2.71 Dye Layer 1 B 43 Gene 5 24.79 0.18.21 −2.47 5.52 Dye Layer 1 B 44 Endo 15.98 1.9 N/A N/A N/A Dye Layer 1B 44 Gene 1 21.82 1.0 5.85 −1.45 2.72 Dye Layer 1 B 44 Gene 2 19.42 0.43.45 −1.00 2.00 Dye Layer 1 B 44 Gene 3 23.11 1.1 7.13 −0.46 1.37 DyeLayer 1 B 44 Gene 4 27.18 0.4 11.20 −1.51 2.84 Dye Layer 1 B 44 Gene 525.32 0.6 9.35 −1.33 2.51 Dye Layer 1 B 46 Endo 16.56 1.5 N/A N/A N/ADye Layer 1 B 46 Gene 1 21.21 1.3 4.65 −2.64 6.23 Dye Layer 1 B 46 Gene2 19.43 0.9 2.87 −1.58 2.98 Dye Layer 1 B 46 Gene 3 23.35 0.2 6.79 −0.801.74 Dye Layer 1 B 46 Gene 4 27.23 0.4 10.67 −2.04 4.10 Dye Layer 1 B 46Gene 5 26.13 0.5 9.57 −1.11 2.15 Dye Layer 1 B 47 Endo 16.27 2.5 N/A N/AN/A Dye Layer 1 B 47 Gene 1 23.04 0.3 6.77 −0.52 1.43 Dye Layer 1 B 47Gene 2 20.52 0.2 4.26 −0.19 1.14 Dye Layer 1 B 47 Gene 3 22.98 1.2 6.71−0.88 1.83 Dye Layer 1 B 47 Gene 4 27.33 0.9 11.07 −1.64 3.12 Dye Layer1 B 47 Gene 5 25.83 0.2 9.57 −1.11 2.16 Dye Layer 1 B 48 Endo 16.19 1.1N/A N/A N/A Dye Layer 1 B 48 Gene 1 21.88 1.1 5.70 −1.60 3.02 Dye Layer1 B 48 Gene 2 20.48 1.4 4.29 −0.15 1.11 Dye Layer 1 B 48 Gene 3 23.810.4 7.63 0.04 0.97 Dye Layer 1 B 48 Gene 4 28.26 1.4 12.08 −0.63 1.55Dye Layer 1 B 48 Gene 5 25.70 0.3 9.52 −1.16 2.23

1. A computer-readable medium containing instructions for controlling acomputer system in the analysis of an experiment to detect RNA or DNA ina sample, by: receiving exported cycle threshold values for a plate ofwells; calculating delta C_(T), delta delta C_(T) and relativetranscriptional change for the sample; and displaying the cyclethreshold values, the delta C_(T), the delta delta C_(T) and therelative transcription change (XRel) of the sample.
 2. A method in acomputer system for analyzing an experiment to detect RNA or DNA from atwo-dimensional plate configuration comprising the steps of: recordingexperiment information for the experiment wherein the experimentinformation comprises an experiment id; specify at least one plate tothe experiment wherein said plate is a real plate or a virtual plate,each said plate comprising a series of wells and dye layers, each saidplate having at least one an FPR set, wherein each said FPR set iscategorized by dye layer or well; create and populate at least one RNAgroup wherein RNA is assigned to the RNA group; receive exportedexperimental cycling results for each said plate including a CT valuefor each FPR set in each said well; calculate delta C_(T), delta deltaC_(T), and XRel values for each said sample RNA; and display the C_(T),the delta C_(T), the delta delta Ct, and the XRel values for each saidsample RNA to detect RNA.
 3. The method of claim 2, further comprisingthe step of characterizing a plate layout.
 4. The method of claim 2,further comprising the step of accessing raw data and managing outliers.5. The method of claim 4, wherein the outliers are managed at the welllevel for said each dye layer.
 6. The method of claim 2, furthercomprising the step of preparing an experiment for a sample wherein theexperiment is a new experiment or an existing experiment.
 7. The methodof claim 2, wherein file information is linked to each said real plate.8. The method claim 2, wherein a plate is linked with each said virtualplate.
 9. The method of claim 2, wherein said experiment informationincludes at least one additional piece of information selected from thegroup of experiment date, dye layer, label, description, notebook page,outlier cutoff, and amplification efficiency.
 10. The method of claim 2,wherein said experimental information includes gene criteria having atleast one criteria selected from the group of species, gene, forwardprimer, probe and reverse primer.
 11. The method of claim 2, wherein oneFPR set is specified per well.
 12. The method of claim 2, wherein theexperiment is multiplexed and one FPR set is specified per each dyelayer
 13. The method of claim 2, wherein one registered RNA is specifiedper well.
 14. The method of claim 2, wherein unregistered RNA isspecified per well.
 15. The method of claim 2, wherein the contents ofthe well is selected from the group of minus RT, plate consistencycontrol, sample, and sample and plate consistency control, and each saidwell contains RNA and the FPR set.
 16. The method of claim 2, whereinthe well type is NTC and the well contains the FPR set.
 17. Aninformation-display apparatus used with a sequence detection systemhaving at least one plate, each plate containing a series of wells andat least one FPR set, each well having at least one dye layer, each dyelayer operating independently for detection of a fluorescent emission ofan up regulator or a down regulator during the polymerse chain reaction,said apparatus comprising: receiving means for receiving informationfrom said sequence detection system, wherein the received informationincludes at least calculated threshold data that represents thedetection of RNA of each said dye layer; calculating means forcalculating a delta calculated threshold, a delta delta calculatedthreshold and a relative transcriptional change for a sample; anddisplaying means for displaying the received information and/or thecalculated sum.
 18. A computer program product for use in connectionwith an information-display apparatus, said computer program comprising:a computer usable medium having a computer readable program meansembodied in said medium comprising a collection of cycle thresholdvalues for each dye layer of each well of a plate for determining thepresence of an RNA or DNA sample, said computer readable program meansfor causing a computer to calculate and display a delta C_(T), a deltadelta C_(T) and a XRel value.
 19. An article of manufacture comprising:a computer usable medium having computer readable program code embodiedtherein for determining the presence of RNA or DNA in a sample containedwithin a dye layer of a well of a plate, the computer readable programmeans in said article of manufacture comprising: computer readableprogram code for causing a computer to effect, with respect to one dyelayer, receiving a C_(T) value and storing said C_(T) value in an arrayof data; computer readable program code for causing the computer tocalculate a delta C_(T), a delta delta C_(T) and a XRel value for eachdye layer, and a computer readable program code for causing the computerto display the delta C_(T), the delta delta C_(T) and the XRel valuesfor the sample.
 20. A program storage device readable by a computer,tangibly embodying a program of instructions executable by the computerto perform method steps for determining the presence of RNA in a sample,by: receiving exported cycle threshold values for a plate of wells; andcalculating a delta C_(T), a delta delta C_(T) and a relativetranscriptional change for the sample; and displaying the cyclethreshold values, and the delta C_(T), the delta delta C_(T) and theXRel values of the sample.
 21. A memory for storing data for access by acomputer readable program being executed on a computer, comprising: adata structure stored in said memory, said data structure includinginformation resident in a database used by the computer readable programand including: experiment information; plate information including rawdata outliers; plate layout; RNA group information; and export fileinformation including C_(T) value.
 22. A computer-readable mediumcontaining a data structure for storing a collection of information todetermine the presence of RNA or DNA in a sample comprising experimentinformation, plate information including raw data outliers, platelayout, RNA group information, export file information, and C_(T)values.
 23. A method in a computer system for calculating and displayingdelta C_(T) values, delta delta C_(T) values, and XRel values in theanalysis of an experiment to detect RNA or DNA from a two-dimensionalplate configuration containing wells, comprising: identify a well type;specify an FPR set for the experiment; specify an RNA group wherein saidRNA group has at least one RNA retrieve a C_(T) value for each well ofeach plate; selecting at least one comparator group wherein saidcomparator group has at least one RNA; and display reports showingcalculated delta C_(T), delta delta C_(T), and XRel.
 24. The method ofclaim 23, further comprising the step of select an endogenous control.